Triple
T38138307
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leaves That Are Green |
E952408
|
entity |
| Predicate | basedOnPoeticImageryOf |
P182632
|
FINISHED |
| Object | seasons |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: seasons | Statement: [Leaves That Are Green, basedOnPoeticImageryOf, seasons]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: basedOnPoeticImageryOf Context triple: [Leaves That Are Green, basedOnPoeticImageryOf, seasons]
-
A.
poeticDepiction
chosen
Indicates that one entity artistically represents or describes another using poetic or figurative language.
-
B.
hasSpiritualImagery
Indicates that something contains or employs imagery related to spiritual, religious, or transcendent themes.
-
C.
usesPoeticLandscapeSystem
Indicates that one entity employs or applies a poetic landscape system in relation to another entity or context.
-
D.
usedPoeticallyFor
Indicates that one entity is employed in a poetic or figurative way to refer to or represent another entity.
-
E.
poeticParaphrasedIn
Indicates that one expression is rendered as a poetic or stylistically embellished paraphrase of another expression.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f76f09a7148190a4b91c0bacdc127a |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69ff7fc835f08190afd1f8129b7a62a2 |
completed | May 9, 2026, 6:41 p.m. |
| PD | Predicate disambiguation | batch_69ff7f2e99ac8190ba372a1358a05a30 |
completed | May 9, 2026, 6:38 p.m. |
Created at: May 3, 2026, 4:21 p.m.